On the Binding Mechanism of Synchronised Visual Events

  • Authors:
  • Jeffrey Ng;Shaogang Gong

  • Affiliations:
  • -;-

  • Venue:
  • MOTION '02 Proceedings of the Workshop on Motion and Video Computing
  • Year:
  • 2002

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Abstract

We address the problem of interpreting visual surveil-lancedata by learning appropriate spatio-temporal sub-spacesof active image regions caused by scene activities.We focus on identifying regions of sustained change forrecognising key stages of a visual behaviour. Our behaviourrepresentation is based on the asynchrony or delay patternsof occurrence among local events which need notbe spatially connected. We use an automatic NormalisedCut structure discovery algorithm with a hybrid similaritycriteria for simultaneously identifying relevant spatio-temporalsubspaces and clustering similar behaviour pat-ternsin those subspaces. We compare the automaticallydiscovered classes with conceptual classes of behaviours ina semi-constrained "Shopping" scenario.